Predictive arithmetic overflow detection

Abstract

A method for arithmetic overflow detection includes receiving a first instruction defined for a first processor having a first base, where the instruction comprises an operator and at least one operand having an operand type. The method also includes indicating whether the at least one operand has potential overflow based at least in part on the operator and the relationship between the operand type and a result type associated with the operator.

Description

CROSS REFERENCE TO RELATED APPLICATIONS[0001]This Application is a continuation-in-part of application Ser. No. 10 / 686,513 filed on Oct. 14, 2003 in the name of inventors Zhiqun Chen and Judith Schwabe and entitled “Optimization of N-Base Typed Arithmetic Expressions”, which is a continuation of application Ser. No. 10 / 002,437 filed Nov. 1, 2001 now U.S. Pat. No. 6,687,898 in the name of inventors Zhiqun Chen and Judith Schwabe and entitled “Optimization of N-Base Typed Arithmetic Expressions”, which is a continuation of application Ser. No. 09 / 439,113 filed Nov. 12, 1999 (now U.S. Pat. No. 6,363,523) in the name of inventors Zhiqun Chen and Judith Schwabe and entitled “Optimization of N-Base Typed Arithmetic Expressions”, commonly assigned herewith.[0002]This application is related to the following:[0003]U.S. patent application Ser. No. 09 / 243,101, filed Feb. 2, 1999 in the name of inventors Joshua Susser and Judith Schwabe and entitled “Object-Oriented Instruction Set for Resource...

AI Technical Summary

Benefits of technology

"The patent describes a method for detecting when a computer instruction may overflow, meaning it may produce incorrect results. This is done by analyzing the type of operands (the parts of the instruction) and the type of result that the instruction produces. The method can help improve the accuracy and reliability of computer instructions."

Problems solved by technology

However, this type widening typically requires more computational stack space.

On resource-constrained devices such as smart cards, there is typically insufficient memory available to perform such computations where type widening takes place.

Additionally, these devices typically have limited memory capacity.

Performing 32-bit operations on data that has been widened to 32-bits is especially inefficient.

Thus, the limited architecture and memory of resource-constrained devices such as smart cards make it impractical or impossible to execute programs where the values have been widened to a larger integral type.

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